Special tips for Art, Design & Architecture 2020 (WORKING COPY)

INTRODUCTION / MOTIVATION

How do I write a DMP? - READ THIS FIRST!

• Read all of the questions first!
• Use a DMP to complement your research plan – avoid overlaps with the research plan!
• The research plan describes the scientific, analytical and methodological processing of data.
• The data management plan describes the technical and administrative management of data.
• To avoid redundancy, refer to your research plan in your DMP and vice versa.
• Use the DMP as a risk evaluation document – it shows that you can recognise, anticipate and handle the risks related to your data management workflow.
• The DMP should be drawn from your own research project – do not copy/paste examples from somewhere else.
• Write only sentences you yourself understand.
• Answer the questions where applicable – if a certain question is not applicable in your case, justify why not.
• Answer at least the main categories – each sub-question does not need to be answered separately.
• Include background information such as the name of the applicant and the project, the project number, the funding programme and the version of the DMP.
• Demonstrate your data management and version control skills, for example, when considering the name of the DMP file.
• Follow the organisation’s or funder’s requirements.

Why should you manage your research data and write a data management plan (DMP)?

• It is good research practice!
• You will reduce the risk of losing your data.
• You will be able to anticipate complex ownership and user rights issues in advance.
• It helps you support open access to create productive future collaborations.
• You will meet your funder’s requirements.
• It helps you save time and money.
• Your DMP reflects your managerial skills as a project leader.

In the DMP context, ‘data’ is understood as a broad term. Data covers all of the information and material your research results are based on. You can concentrate on the data, which is your responsibility.

Your DMP should describe how you will manage the data throughout the life cycle of your research. The DMP is a living document, which should be updated as the research project progresses.

Your research data management practices should aim to produce reusable data, which follows FAIR principles, that is, your data will be Findable, Accessible, Interoperable and Re-usable.

Good luck with your DMP!

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide. Check also your institutional guides and policies concerning the data management.

Research data in the field of art, design and architecture

In the DMP data is understood as a broad term including:

• Work of art as a part of the research material
• Printed,  notated, or sheet music with annotations and remarks that reform new interpretations (electronic form and in many cases analytic form) presented in a concert
• Pictures from manuscripts in electronic or analytic form
• Archival material
  
• A new developed form of a musical instrument (e.g. different forms of kantele, or quarter tone piano)
• The knowledge how to play an instrument
• Knowledge by experience
  

Ohjeesta saatu yleinen palaute ja kehitysehdotukset

• Suomenkielistä ohjetta kaivattiin omaan käyttöön tehtäviä aineistonhallintasuunnitelmia varten, koska englanninkielinen DMP-termistö voi olla vierasta tutkijalle
• Ohjeet ohjaavat miettimään aineistonhallintaan ja omaan tutkimustyöhön liittyviä asioita, vaikka rahoitusta ei hakisikaan
• Laadullinen aineisto pitäisi saada paremmin näkyviin ohjeeseen ja esimerkkeihin
  
  
• Olisiko mahdollista valita ohjeet datatyypin mukaan, esim. piirustusaineiston valitsemalla saisi siihen liittyvän ohjeistuksen näkyviin?
• Kysymykset soveltuvat myös haastateltavan aineistoihin. Niitä tuskin tarvitsee muuttaa tai niitä ei tarvitse lisätä. Taiteelliselle tutkimukselle voisi rakentaa oman/omia ohjetekstejä ja esimerkkejä erityisesti kohtaan 1.
• Ohje-dokumentti oli aivan käsittämätön tutkijan mielestä. Ohjeen yksin luettuaan tutkija tunsi itsensä tyhmäksi ja vasta keskustelu haastattelijan kanssa avasi ohjeen ja teki sen ymmärrettäväksi.  
• Konkreetteja esimerkkejä kaivattiin kohtiin 1, 2. Erityisesti kohta 2.2. herätti keskustelua mutta pohdinnoista huolimatta tutkija ei pystynyt kuvaamaan miten ohjeen kirjoittaisi uusiksi.
  
• Ohjeistukset ja esimerkit ovat aika pitkiä. Näihin toivottiin yksinkertaistusta ja lisää rautalangasta vääntämistä. Tutkijan mielestä moni on hakuvaiheessa jo niin stressaantunut ja väsynyt, että vähänkään monimutkaisemman manuaalin/ohjeistuksen lukeminen voi tuntua tässä vaiheessa ylivoimaiselta urakalta. Tämä voisi helpottaa asettelullakin siten, että jokaisen asian ydin esitettäisiin mahdollisimman yksinkertaisesti. Esim. Digital video data, photographs, postal and electronic survey data jne. ja sitten pienen välin jälkeen voi olla tarkentavaa selitystä esimerkkeineen. Tutkija kokee tärkeäksi, että juuri häntä kiinnostava kohta (type of data) löytyy nopealla vilkaisulla, etä vaadi laajempien tekstien kahlaamista.
• Tips for best practices -osio koettiin hyväksi ja siihen kannattaisi kerätä lähestulkoon kaikki mahdolliset keinot, joilla jokainen kohta on helpointa ja nopeinta täyttää sekä suorittaa. Esimerkiksi "vaihe 1, 2, 3, 4, jne. -jaottelu voisi olla toimiva, mikäli sellainen on mahdollista toteuttaa. Näin voisi aina rastia, mitkä kohdat on tehty ja mitkä ei. Tämä osio tekee monista muuten abstrakteiksi koetuista asiasisällöistä helpommin hahmotettavia.
• Taiteellisen tutkimuksen tekijöille ohje oli vaikeaselkoinen. TaiY:ssa tehtyyn lomakekyselyyn tuli erittäin vähän vastauksia, eikä aikataulu antanut myöten haastatteluille.

1.1 What kinds of data is your research based on? What data will be collected, produced or reused? What file formats will the data be in? Additionally, give a rough estimate of the size of the data produced/collected.

Briefly describe what types of data you are collecting or producing. In addition, explain what kinds of already existing data you will (re)use. List, for example, the types of texts, images, photographs, measurements, statistics, physical samples or codes.

Categorise your data in a table or with a clear list, for example:
A) data collected for this project,
B) data produced as an outcome of the process,
C) previously collected existing data which is being reused in this project,
D) managerial documents and project deliverables, and so on.

The categorisation follows the license policy of your data sets. For example, briefly describe the license according to which you are entitled to (re)use the data. The categorisation can form a general structure for the rest of the DMP.

List the file formats for each data set. In some cases, the file formats used during the research project may differ from those used in archiving the data after the project. List both. The file format is a primary factor in the accessibility and reusability of your data in the future.

In the DMP, what is important is to describe the required disk space, not how many informants participated in the project. A rough estimation of the size of the data is sufficient, for example, less than 100 GB, approx. 1 TB or several petabytes.

Tips for best practices

• Use a table or bullet points for a concise way to present data types, file formats, the software used and the size of the data.
• Examples of file formats are .csv, .txt, .docx, .xslx and .tif.
• Make sure to describe any special or uncommon software necessary to view or use the data, especially if the software is coded in your project.
• You can also estimate the increase in data production or collection during the project for a specific time period: "The project is producing/collecting approximately 100 GB of data per week."

AVOID OVERLAPS WITH THE RESEARCH PLAN! Data analysis and methodological issues related to data and materials should be described in your research plan..

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

The categorisation of your data sets in this first section outlines a structure for the following sections in your DMP. Concentrate on data and materials that you collect or produce in your project. Original works of art in various collections curated by a responsible organisation (e.g. museum or archive) can be mentioned briefly, if necessary. However, avoid overlapping with the research plan. Focus here especially on describing the types of data whose managing (e.g. storing, archiving, publishing) is your responsibility. 

An example from the field of design

A) Background material (sometimes research subject itself)

1. videos and pictures about a usage situation
2. usability studies

B)  The data that you are reusing

1. standards and instructions

C) The data that your research produces

1. interviews (audio recordings, video recordings, transcriptions)
2. questionnaires
3. answers to questionnaires
4. hand-drawn pictures that are turned into photographs and 3-D models
5. post-it notes that are turned into PowerPoint presentations

An example concerning file formats:

C) The data that your research produces

1. interviews
   1. audio recordings: wav, flac
   2. video recordings: mpeg, mp4
   3. transcriptions: docx that is saved as a txt file for long term storage
   4. questionnaires : docx, html
   5. answers to questionnaires: xlsx that is saved as a csv file for long term storage
   6. hand-drawn pictures that are turned into
      1. photographs: tif
      2. 3-D models: dwg
      3. Post-it notes that are turned into PowerPoint presentations: pptx that is saved as a pdf file for archiving. 

Tips for best practices

• Use a table or bullet points for a concise way of presenting data types, file formats, the software used and so on.
• Use adequate file formats which fit your project's needs – that is, check that the file format requirements are in line with your research plan, questions and target of research. If high resolution file formats are necessary, then use them - but explain why they are necessary and how you will handle them.

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• Research material on research dataa tutumpi termi
  
  • → (ks. johdannon data-määritelmä)
• Data vie ajatukset määrälliseen dataan mutta arkkitehtuurissa kyse voi olla esim. piirustuksista, haastatteluista, videoista, ääninauhoista, kirjallisuudesta, kartoista, valokuvista, hankedokumenteista, sosiaalisen median aineistoista, ihmisten tuottamasta paikkatiedosta jne.
  • → (ks. johdannon data-määritelmä)
• taidealojen tutkimuksessa aineistoa ei ainoastaan kerätä "collected" vaan aktiivisesti tuotetaan "created"
  • → (kuten lähes kaikilla muillakin aloilla)
• Ohje on ymmärrettävä, mutta esimerkit taidealoilta puuttuvat. Taidealojen aineisto voi olla huomattavan monimuotoista (artistic, practice-based research, tuotekehitys, erilaiset produktiot, omat teokset, muiden teokset, näyttelyjen sarjat, tekijän reflektio, yleisön reflektio...) Ohjeen perusteella vastaajalle epävarmaa ymmärretäänkö kaikki tämä aineistoksi.
  • → (ks. johdannon data-määritelmä)
• Taiteellisessa toimintatutkimuksessa, mitä haastateltava edustaa, syntyy hyvin monipuolisia aineistoja; autenttinen taideteos tai taiteellista toimintaa. → (ks. johdannon data-määritelmä)
  
• Hyvin tuotu esiin heti alkuun se, ettei

  metodeja tarvitse uudelleen kirjata, vaan voi viitata tutkimussuunnitelmaan.

• Taiteellisen tutkimuksen tekijöille ei aina ole selvää, mitä on se tutkimusaineisto, jota tässä ohjeessa tarkoitetaan. Tarvittaisiin lisää esimerkkejä (Esim. written documents (newspapers, magazines, books, diaries, written memoirs of artists), images, digital audio/video files, audio/video tapes, text corpus, websites, software ym. ym. → (ks. johdannon data-määritelmä)

• Tutkimusaineisto ei ole välttämättä sähköisessä muodossa, vaan esim. muistiinpanoja tai fyysisinä kappaleina
• Esimerkkitiedostomuotoina voisi olla myös kuville tai CAD-tiedostoille suositellut tiedostomuodot
• Arkkitehtuurissa käytetään paljon 3D kuvaa ja mallinnusta. Tutkija kaipasi tieto onko 3Dlle standardiformaatti: Mitä tapahtuu jos toimistojen digiarkistot eivät ole tutkimuksen käytössä teidostotyyppien ja erityisohjelmien versiomuutosten vuoksi.
• Kaipaa täsmennystä: tarkoitetaanko vain digitaalista tallennetta/dokumentaatiota vai myös alkuperäisaineistoa? Teokset, näyttelyt? Entä kun teokseen liittyy oleellisesti sen ympäristö tai osallistujat? (→ Data is understood as a broad term that includes ”all information that is needed to replicate a study ---, and everything that is potentially useful for others.” – Sarah Jones /DCC)
• Toimintatutkimukseen liittyy video- ja kuvamateriaalia, haastatteluaineistoja, kyselyitä, osallistuvaa havainnointia tutkimuspäiväkirjoa. Näin ollen myös aineistoformaatit ovat moninaisia. Katoavan taiteen ongelma, kun jokin ainutkertainen esitys dokumentoituna ei kuitenkaan ole sama kuin esitystilanteessa.

1.2 How will the consistency and quality of data be controlled?

Explain how the data collection, analysis and processing methods used may affect the quality of the data and how you will minimise the risks related to data accuracy.

Data quality control ensures that no data is accidentally changed and that the accuracy of the data is maintained over its entire life cycle. Quality problems can emerge due to the technical handling, converting or transferring of data, or during its contextual processing and analysis.

Tips for best practices

• Transcriptions of audio or video interviews should be checked by someone other than the transcriber.
• Analog material should be digitised in the highest resolution possible for accuracy.
• In all conversions, maintaining the original information content should be ensured.
• Software-producing checksums should be used.
• Organise training sessions and set guidelines to ensure that everyone in your research group can implement quality control and anticipate the risks related to the quality of the data.

AVOID OVERLAPS WITH THE RESEARCH PLAN! Issues related to data analysis, methods and tools should be described in your research plan, that is, do not include, for example, instrument calibration descriptions here.

.

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

Describe the quality control methods of the data management. Note that the quality of research methods will be described in the research plan.

Tips for best practices

• Describe how you will take care of data quality and completeness while converting from analog to digital format (no data loss, etc.)
• Transcriptions of audio or video interviews should be checked by someone other than the transcriber.
• Analog material should be digitised in as high resolution as possible for accuracy.
• In all conversions, maintaining the original information content should be ensured.
  

• Moniulotteinen kysymys, mutta sinänsä selkeä. Kaipaa kuitenkin esimerkkejä tai ohjeen konkretisointia. 
• Taidealoilla konsistenssi ei välttämättä ole laadun tae aineiston osalta. Päinvastoin - kiinnostavinta tutkimuksen näkökulmasta voi olla ristiriitaisuus ja yllättävyys. Kysymys on tässä mielessä hämmentävä.
• Tässäkin laadullinen data jää huomioimatta → Tässä puhutaan nähdäkseni yleisemmällä tasolla; eli tältä osin sama ohje koskee niin laadullista kuin määrällistä tutkimusta

2.1 What legal issues are related to your data management? (For example, GDPR and other legislation affecting data processing.)

All types of research data involve questions of rights and legal and ethical issues. Demonstrate that you are aware of the relevant legislation related to your data processing. If you are handling personal or sensitive information, describe how you will ensure privacy protection and data anonymisation or pseudonymisation.

Tips for best practices

• Check your institutional ethical guidelines, data privacy guidelines and data security policy, and prepare to follow the instructions that are given in these guidelines.
• If your research is to be reviewed by an ethical committee, outline in your DMP how you will comply with the protocol (e.g., how you will remove personal or sensitive information from your data before sharing data to ensure privacy protection).
• Will you process personal data? If you intend to do so, please detail what type of personal data you will collect.
• All data related to an identified or identifiable person is personal data. Information such as names, telephone numbers, location data and information on the congenital diseases of the individual's grandparents is personal data.
• Office of the Data Protection Ombudsman (https://tietosuoja.fi/en/processing-of-personal-data)

AVOID OVERLAPS WITH THE RESEARCH PLAN! Details of the ethical issues, the ethical committee statements and the use of laboratory animals should be described in the research plan..

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

Example of an answer

The research uses pictures of a usage situation as background material and produces materials from interviews and questionnaires. Research materials include materials that observe people in a private setting. Explicit consent is sought from the participants before the project starts and data is collected for the materials to be made public and available for reuse.

Links to general guides

• Art University Copyright Advice: http://copyright.aalto.fi/en/
• The national guide of how to manage sensitive information: http://doi.org/10.5281/zenodo.1298461
• Consent for data sharing: https://www.ukdataservice.ac.uk/manage-data/legal-ethical/consent-data-sharing
  

Tips for best practices

• Location and ownership information of an art work in a private collection is sensitive information
  
  

• Ohjeessa voisi selkeästi listata näkökohdat, joita tässä yhteydessä on otettava huomioon
• Kohta 4 (nykyään siis kohta 2) tuntuu olevan väärässä paikassa; loogisempi paikka olisi esim. kohdan 2 jälkeen
• Kysymys 4 ei sovi ajallisesti tähän kohtaan, koska etiikkaan liittyviä kysymyksiä on mietittävä jo aikaisemmin.
  • ==> ELI YLLÄ OLEVAT KOMMENTIT ON HUOMIOITU UUDESSA KANSALLISESSA RAKENTEESSA, JOKA ON TÄSSÄ TAULUKOSSA

2.2 How will you manage the rights of the data you use, produce and share?

Describe how you will agree upon the rights of use related to your research data – including the collected, produced and (re)used data of your project. Here, you can employ your categorisation in the first question. Each of these categories involves different rights and licenses. Describe the transfer of rights procedures relevant to your project. Describe confidentiality issues if applicable in your project.

Tips for best practices

• Check your organisational data policy for ownership, the right of use and the right to distribute.
• Have you gained consent for data preservation and sharing?
• Agreements on ownership and rights of use should be made as early as possible in the project life cycle.
• Consider the funder's policy.
• It is recommended to make all of the research data, code and software created within a research project available for reuse, e.g., under a Creative Commons (

https://creativecommons.org/choose/), GNU (https://www.gnu.org/licenses/gpl-3.0.en.html) or MIT license (https://opensource.org/licenses/MIT), or under another relevant license.

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

A) Background material and data you are reusing

Describe the permissions you have for using and distributing the material, and making it openly available.

B) The data that your research produces

Describe who owns the copyright of the research material, what use permissions the materials have, and in case of any third party materials who can issue permissions to reuse it.

These issues should be solved already at the planning stage of the research project. If ownership issues have not been considered early enough in the research life cycle, archiving, publishing and reusing the data may become impossible. Check your organizational data policy for ownership guidelines and consider the funder's policy on copyrights or IPR.

Example of answers

Researchers have permission to access and cite all of the material in research. Materials with a CC-BY-license researchers have permission to modify, share and make them available for reuse as long as the copyright holders. Materials with an all rights reserved status researchers cannot be shared.

The data that the research produces includes audiovisual and other materials whose copyright is owned by the researchers. All parties explicitly and jointly choose and agree to sharing the material with a CC-BY-license.

Links

•  https://www.ukdataservice.ac.uk/manage-data/rights/sharing

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• Tässä kaipaa lähinnä tietoa oman yliopiston ja rahoittajan menettelytavoista
• Kaivattiin tietoa oman yliopiston käytännöistä datan omistajuuden suhteen

3.1 How will you document your data in order to make the data findable, accessible, interoperable and re-usable for you and others?  What kind of metadata standards, README files or other documentation will you use to help others to understand and use your data?

Data documentation enables data sets and files to be discovered, used and properly cited by other users (human or computer). Documentation includes essential information regarding the data, for example, where, when, why and how the data were collected, processed and interpreted. Without the proper documentation, your data is useless. Describe the tool, such as Qvain, that you will use to describe your data sets. Do not mention metadata standards if you do not use them. You can anticipate the open accessibility of your data and its description already here. However, a detailed description of which part of your data can be set openly available will be included in Section 5 below.

AVOID OVERLAPS WITH THE RESEARCH PLAN! The data-level documentation (https://www.ukdataservice.ac.uk/manage-data/document/data-level.aspx) and details about experiments, analytical methods and the research context belong to the research plan. In the DMP you should concentrate on the study-level documentation (https://www.ukdataservice.ac.uk/manage-data/document/study-level.aspx).

Tips for best practices

• Describe all the types of documentation (README files, metadata, etc.) you will provide to help secondary users to find, understand and reuse your data.
• Following the FAIR (https://www.force11.org/group/fairgroup/fairprinciples) principles will help you ensure the Findability, Accessibility, Interoperability and Re-usability of your data.
• Know the minimum requirements for data documentation; see, for example, Qvain Light (https://www.fairdata.fi/en/qvain/qvain-light-user-guide/).
• Use research instruments, which create standardised metadata formats automatically.
• Identify the types of information that should be captured to enable other researchers to discover, access, interpret, use and cite your data.

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

Describe here how you document your data in a way that the description will be understandable also to others who were not involved in data creation. Examples about the content of documentation and metadata:

• creator, performer, audience
• name of the object
• location, creation date, size
• material, format, versions (drafts, final, published etc)
• photographer, videographer, editor, documentor...

Links to general guides about documentation and metadata

• ACADI- Association of Curators of Art and Design Images' metadata standards for images: https://acadi.wordpress.com/image-curation/metadata-standards/
• VRA Core - A data standard for the description of images and works of art and culture: http://www.loc.gov/standards/vracore/schemas.html

The Arts and Humanities Data Service (AHDS) has published an online guide resource for visual arts: "Creating digital resources for the visual arts: standards and good practice"  (https://vads.ac.uk/guides/creating_guide/contents.html) 

Tips for best practices

• If you publish the data through a specific archive, follow the documentation guidelines of the archive.
• Describe how you will preserve modifications made to data over time since their original creation and identification of different versions of data sets.

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• Metadatan tuottaminen laadullisille aineistoille tai kuville jää epäselväksi, minkälaista ja kuinka tarkkaa metadataa niistä pitäisi tallentaa?
• Laadullisesta aineistosta voisi olla esimerkki määrällisen aineiston rinnalla sekä kohdassa 2.1 että 2.2
• Kysymys ohjeenkin kanssa on epämääräinen ja laaja - täydennettävä vähintäänkin metadatan käsitteen avaamisella tai esimerkeillä
• Kysymyksen merkitys jäi hämäräksi

• Ei avautunut aluksi ollenkaan. Kohta tuli ymmärrettäväksi kun käytettiin esimerkkinä tietojen tallentamista tietokantaan ja kannan kenttien nimiä metadatana. Lisäksi puhuttiin siitä, että oheen voi usein tallentaa dokumentin, jossa kuvailee materiaaleja / aineistoja ja niiden syntykontekstia laadullisesti.

• ==> TÄSSÄ VOISI OLLA KYLLÄ VIITTAUS KANSALLISEEN OHJEESEEN, JOSSA NYT SELKEÄMPI KUVAUS TÄMÄN KYSYMYKSEN TAVOITTEESTA

4.5. kokouksessa tähän ehdotettiin seuraavaa: "reusable arkkitehtuurissa?  tekstiehdotus: -and reusable as a source to yourself and others" MUTTA MIHIN KOHTAAN TÄMÄ SOPII?

4.1 Where will your data be stored, and how will the data be backed up?

Describe where you will store and back up your data during your research project. Explain the methods for preserving and sharing your data after your research project has ended in more detail in Section 5.

Consider who will be responsible for backup and recovery. If there are several researchers involved, create a plan with your collaborators and ensure safe transfer between participants.

Show that you are aware of the storing solutions provided by your organisation. Do not merely refer to IT services. In the end, you are responsible for your data, not the IT department or the organisation.

Tips for best practices

• The use of a safe and secure storage provided and maintained by your organisation’s IT support is preferable.
• Do NOT USE external hard drives as the main storing option.

In 4.1 no special tips for Art, Design and Architecture; see generic DMPTuuli guidance.

• Miten pitäisi huomioida aineisto, joka ei ole sähköisessä muodossa, esim. kirjat tai havaintomuistiinpanot?
• Jälleen nousi esiin kysymys alkuperäisaineiston ja digitaalisen tallenteen välisestä suhteesta - tuleeko tässä ajatella molempia?
• Esimerkiksi ehdotettiin tilannetta, jossa osa aineistosta on digitaalista + fyysistä "omaa" ja osa 3 osapuolen fyysistä + digitaalista → tulisi esille arkkitehtuurin tutkimus, jossa valtava aineistodiversiteetti. Tämä esimerkki auttaisi myös kohtien 4 ja 5 ohjeiden ja esimerkkien kirjoittamisessa.

4.2 Who will be responsible for controlling access to your data, and how will secured access be controlled?

It is essential to consider data security issues, especially if your data include sensitive data, personal data, politically sensitive information or trade secrets. Describe who has access to your data, what they are authorised to do with the data, or how you will ensure the safe transfer of data to your collaborators.

Tips for best practices

• Access controls should always be in line with the level of confidentiality involved.

In 4.2 no special tips for Art, Design and Architecture; see generic DMPTuuli guidance.

• Lisäohjeistukseksi riittäisi linkki oman organisaation täsmälliseen ohjeeseen

5.1 What part of the data can be made openly available or published? Where and when will the data, or its metadata, be made available?

Describe whether you will make openly available or publish all your data or only parts of the data. If your data or parts of the data cannot be opened, explain why.

In the case of sensitive data, which cannot be opened, describe the opening of its metadata. Describe the secured preservation procedure of sensitive data in Section 5.2.

The openness of research data promotes its reuse.

Tips for best practices

• You can publish a description (i.e., the metadata) of your data without making the data itself openly available, which enables you to restrict access to the data.
• Publish your data in a data repository or a data journal.
• Check re3data.org (https://www.re3data.org/) to find a repository for your data.
• Remember to check the funder, disciplinary or national recommendations for data repositories.
• It is recommended to make all of the research data, code and software created within a research project available for reuse, for example, under a Creative Commons (https://creativecommons.org/choose/), GNU (https://www.gnu.org/licenses/gpl-3.0.en.html) or MIT license (https://opensource.org/licenses/MIT), or under another relevant license.
• Consider using repositories or publishers, which provide persistent identifiers (PID) to enable access to the data via a persistent link (e.g. DOI, URN).

AVOID OVERLAPS WITH THE PUBLICATION PLAN! The research article publication does not equal data publication. The data journal is a publication forum specialised in publishing research data.

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

Focus here on the data which your research produces and for which you have the responsibility or rights of publishing or setting openly available. If you are using research material from archives or museums, you can mention here about the availability and accessibility of the material.

Tips for best practises

• Follow your institutional recommendations for data sharing
• Find the appropriate subject repository: Registry of research data repositories: www.re3data.org
• Or use general data repository like Zenodo: www.zenodo.org
• Remember to check funder, disciplinary or national recommendations for data repositories.
• It is recommended to make all research data, code and software created within a research project available for reuse, e.g., under Creative Commons, GNU, MIT or another relevant license.

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• Epäselvää viittaavatko kysymykset ja ohjeet sekä hankkeen toteutukseen että sen jälkeiseen aikaan
• Kumpaa dataa tarkoitetaan, raakadataa vai siitä syntynyttä johdannaisdataa/valmiiksi analysoitua dataa?

5.2 Where will data with long-term value be archived, and for how long?

Briefly describe what part of your data you will preserve and for how long. Categorise your data sets according to the anticipated preservation period:

A) Data to be destroyed upon the ending of the project
B) Data to be archived for a verification period, which varies across disciplines, e.g., 5–15 years
C) Data to be archived for potential re-use, e.g., for 25 years
D) Data with long-term value to be archived by a curated facility for future generations for tens or hundreds of years

Describe which part of the data you will dispose of after the project and how you will destroy the data. Describe the access policy to the archived data. Consider using archives with a curation policy.

Tips for best practices

• Remember to check funder, disciplinary or national recommendations for data archives.

NB! Special tips for Art, Design & Architecture is an addition to the national generic DMPTuuli guidance - please, read this guide beside the national guide.

Please describe which parts of your data are valuable enough to warrant long-term preservation (over 15 years). Describe how the data with the long-term value will be made available. Data selected for the long-term preservation will normally be submitted to the data archive.

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• Jälleen kysymys siitä, käsittääkö kohta sekä alkuperäisaineistoa että digitaalisia kopioita
• Onko kyse raakadatasta vai analysoidusta tai käsitellystä datasta?

Summarise here all the roles and responsibilities described in the previous answers.

Tips for best practices

• Outline the roles and responsibilities for data management/stewardship activities, for example, data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Name the responsible individual(s) where possible.
• For collaborative projects, explain the co-ordination of data management responsibilities across partners.
• Indicate who is responsible for implementing the DMP and for ensuring that it is reviewed and, if necessary, revised.
• Consider scheduling regular updates of the DMP.

• Laaja kysymys. Miten pitkälle aineiston elinkaari tulee ajatella? Esim. taideteosten ikä voi ylittää tutkijan iän.
• Tässä voisi tarjota esimerkkejä käsittelystä, säilytyksestä ja jakamisesta.

Estimate the resources needed (for example, financial and time) to manage, preserve and share the data. Consider the additional computational facilities and resources that need to be accessed, and what the associated costs will amount to.

Tips for best practices

• Remember to specify your data management costs in the budget, according to funder requirements.